Go Channel Patterns - Fan-out, Fan-in, and Pipeline

Need to process data concurrently in Go but unclear how to structure goroutines and channels for different concurrency patterns.

Common channel patterns:

// Pipeline: chain processing stages
func generate(nums ...int) <-chan int {
    out := make(chan int)
    go func() {
        for _, n := range nums {
            out <- n
        }
        close(out)
    }()
    return out
}

func square(in <-chan int) <-chan int {
    out := make(chan int)
    go func() {
        for n := range in {
            out <- n * n
        }
        close(out)
    }()
    return out
}

// Usage: pipeline
for v := range square(generate(1, 2, 3, 4)) {
    fmt.Println(v) // 1, 4, 9, 16
}

// Fan-out: multiple goroutines read from same channel
// Fan-in: merge multiple channels into one
func fanIn(channels ...<-chan int) <-chan int {
    var wg sync.WaitGroup
    merged := make(chan int)
    for _, ch := range channels {
        wg.Add(1)
        go func(c <-chan int) {
            defer wg.Done()
            for v := range c {
                merged <- v
            }
        }(ch)
    }
    go func() {
        wg.Wait()
        close(merged)
    }()
    return merged
}

// Worker pool with bounded concurrency
func workerPool(jobs <-chan Job, results chan<- Result, numWorkers int) {
    var wg sync.WaitGroup
    for i := 0; i < numWorkers; i++ {
        wg.Add(1)
        go func() {
            defer wg.Done()
            for job := range jobs {
                results <- process(job)
            }
        }()
    }
    go func() {
        wg.Wait()
        close(results)
    }()
}

Channels are Go's primary synchronization mechanism. These patterns compose to build complex concurrent systems from simple, testable stages.

Building concurrent Go applications